Nowadays, object identification technique can find many uses in many technical fields, such as the analysis of satellite photographs, automation, moving pictures compression and surveillance system. So far there have been a great number of techniques for recognizing an object in an image. One may enumerate, for example, template matching method, statistical pattern recognition method, structural pattern recognition method and neuron network, etc.
One of the objects to be identified is the human body itself, especially the human face. In Haiyuan Wu's “Face Detection and Rotations Estimation Using Color Information”, the 5.sup.th IEEE International Workshop on Robot and Human Communication, 1996, pp 341-346, which is incorporated herein by reference, is disclosed a template matching method for detecting the human face. The effect of the method depends too much on the quality of the image to be detected, especially on the lighting conditions and the complexity of the background. The face differences between different races also affect the detection.
In some other methods, a human face may be detected from an image through detecting first its features (such as the eyes, the mouth and the nose, etc.). In Kin-Man Lam's “A Fast Approach for Detecting Human Faces in a Complex Background”, Proceedings of the 1999 IEEE International Symposium on Circuits and System, 1998, ISCAS'98 Vol. 4, pp 85-88, which is incorporated herein by reference, is disclosed a method for detecting eyes, wherein a plurality of areas are assumed as possible eyes firstly, then they are checked according to some conditions to verify the real eye areas. The efficiency of this method is low because in an image there are too many possible eye areas (eye candidates).
To improve said prior art, the assignee has developed an image processing method and apparatus, system and storage system, which were disclosed in pending CN patent application No.00127067.2 (Publication No. CN1343479A) filed on Sep. 15, 2000, and incorporated herein by reference. Using the method, one can get a list of candidate eye areas in an image. Then by matching the candidate eyes into pairs, one can get a list of candidate human face areas.
Among said candidate eye areas, however, there are some false eye areas. As a result, among said candidate human face areas, there are also some false face areas. Said false eye areas or false face areas should be excluded.
To this end, in another pending CN patent application No.01132807.x, titled “Image Processing Method and Apparatus, System and Storage System”, filed on Sep. 6, 2001, the assignee provided a method for eliminating the non-face areas among the candidate face areas, by means of analyzing an annular portion of each candidate face area.